18. Statistical Methods for Healthcare Economic Evaluation

  1. Frederick W. Faltin4,
  2. Ron S. Kenett5 and
  3. Fabrizio Ruggeri6
  1. Caterina Conigliani1,
  2. Andrea Manca2 and
  3. Andrea Tancredi3

Published Online: 30 JUL 2012

DOI: 10.1002/9781119940012.ch18

Statistical Methods in Healthcare

Statistical Methods in Healthcare

How to Cite

Conigliani, C., Manca, A. and Tancredi, A. (2012) Statistical Methods for Healthcare Economic Evaluation, in Statistical Methods in Healthcare (eds F. W. Faltin, R. S. Kenett and F. Ruggeri), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119940012.ch18

Editor Information

  1. 4

    The Faltin Group, Cody, WY, USA

  2. 5

    The KPA Group, Raanana, Israel

  3. 6

    CNR IMATI, Milan, Italy

Author Information

  1. 1

    Department of Economics, University of Roma Tre, Rome, Italy

  2. 2

    Centre for Health Economics, The University of York, York, UK

  3. 3

    Department of Methods and Models for Economics, Territory and Finance, University of Roma ‘La Sapienza’, Rome, Italy

Publication History

  1. Published Online: 30 JUL 2012
  2. Published Print: 31 AUG 2012

ISBN Information

Print ISBN: 9780470670156

Online ISBN: 9781119940012

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Keywords:

  • complex decision analysis models;
  • cost-effectiveness acceptability curve (CEAC);
  • cost-effectiveness data;
  • healthcare economic evaluation;
  • probabilistic sensitivity analysis;
  • statistical methods

Summary

This chapter describes the statistical issues associated with the conduct of healthcare economic evaluation studies, considering both the analysis based on a single trial and the use of Bayesian comprehensive decision analytic models. The chapter also discusses the role of probabilistic sensitivity analysis and Bayesian evidence synthesis. The difficulty of producing realistic probabilistic models for the underlying population distribution of costs has made very attractive the possibility of considering nonparametric or semiparametric methods, which might be applied without specifying such a population distribution. Two simple nonparametric methods are widely used in the context of cost-effectiveness analysis. The first one is based upon assuming that the sample mean follows a normal distribution. The second nonparametric method that is often used is the bootstrap. Healthcare policy makers are required to use the limited resources as efficiently as possible, given the financial pressure under which many healthcare systems currently operate.

Controlled Vocabulary Terms

Bayesian estimation; probability distribution; sensitivity analysis; statistical methods